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Understanding occupational safety and health surveillance: expert consensus on components, attributes and example measures for an evaluation framework

BACKGROUND: Occupational safety and health (OSH) surveillance systems track work-related fatalities, injuries and illnesses as well as the presence of workplace hazards and exposures to inform prevention efforts. Periodic evaluation is critical to the improvement of these systems to meet the demand...

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Autores principales: Yang, Liu, Branscum, Adam, Kincl, Laurel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8922762/
https://www.ncbi.nlm.nih.gov/pubmed/35287647
http://dx.doi.org/10.1186/s12889-022-12895-6
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author Yang, Liu
Branscum, Adam
Kincl, Laurel
author_facet Yang, Liu
Branscum, Adam
Kincl, Laurel
author_sort Yang, Liu
collection PubMed
description BACKGROUND: Occupational safety and health (OSH) surveillance systems track work-related fatalities, injuries and illnesses as well as the presence of workplace hazards and exposures to inform prevention efforts. Periodic evaluation is critical to the improvement of these systems to meet the demand for more timely, complete, accurate and efficient data processing and analysis. Despite the existence of general guidance for public health surveillance evaluation, no tailored guidance exists for evaluating OSH surveillance systems to date. This study utilized the Delphi technique to collect consensus among experts in the United States on surveillance elements (components, attributes and measures) to inform the development of a tailored evaluation framework. METHODS: A Delphi study approach with three survey rounds invited an expert panel to rate and comment on potential OSH surveillance evaluation framework elements, resulting in an optimal list of elements through the panel’s consensus. Additionally, experts completed a review of OSH surveillance systems they worked with and answered questions regarding the development of an evaluation framework. Descriptive statistics of the ratings were compiled for the Delphi process. Major themes from experts’ comments were further identified using content analysis to inform contextual information underlying their choices. RESULTS: Fifty-four potential experts across the United States were contacted to participate in the Delphi study. Ten experts began the first survey round with eight then seven experts continuing in the subsequent rounds, respectively. A total of 64 surveillance components, 31 attributes, and 116 example measures were selected into the final list through panel consensus, with 134 (63.5%) reaching high consensus. Major themes regarding current OSH surveillance focused on resources and feasibility, data collection, flexibility, and the inter-relatedness among elements. CONCLUSIONS: A Delphi process identified tailored OSH surveillance elements and major themes regarding OSH surveillance. The identified elements can serve as a preliminary guide for evaluating OSH surveillance systems. A more detailed evaluation framework is under development to incorporate these elements into a standard yet flexible approach to OSH surveillance evaluation. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-022-12895-6.
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spelling pubmed-89227622022-03-22 Understanding occupational safety and health surveillance: expert consensus on components, attributes and example measures for an evaluation framework Yang, Liu Branscum, Adam Kincl, Laurel BMC Public Health Research BACKGROUND: Occupational safety and health (OSH) surveillance systems track work-related fatalities, injuries and illnesses as well as the presence of workplace hazards and exposures to inform prevention efforts. Periodic evaluation is critical to the improvement of these systems to meet the demand for more timely, complete, accurate and efficient data processing and analysis. Despite the existence of general guidance for public health surveillance evaluation, no tailored guidance exists for evaluating OSH surveillance systems to date. This study utilized the Delphi technique to collect consensus among experts in the United States on surveillance elements (components, attributes and measures) to inform the development of a tailored evaluation framework. METHODS: A Delphi study approach with three survey rounds invited an expert panel to rate and comment on potential OSH surveillance evaluation framework elements, resulting in an optimal list of elements through the panel’s consensus. Additionally, experts completed a review of OSH surveillance systems they worked with and answered questions regarding the development of an evaluation framework. Descriptive statistics of the ratings were compiled for the Delphi process. Major themes from experts’ comments were further identified using content analysis to inform contextual information underlying their choices. RESULTS: Fifty-four potential experts across the United States were contacted to participate in the Delphi study. Ten experts began the first survey round with eight then seven experts continuing in the subsequent rounds, respectively. A total of 64 surveillance components, 31 attributes, and 116 example measures were selected into the final list through panel consensus, with 134 (63.5%) reaching high consensus. Major themes regarding current OSH surveillance focused on resources and feasibility, data collection, flexibility, and the inter-relatedness among elements. CONCLUSIONS: A Delphi process identified tailored OSH surveillance elements and major themes regarding OSH surveillance. The identified elements can serve as a preliminary guide for evaluating OSH surveillance systems. A more detailed evaluation framework is under development to incorporate these elements into a standard yet flexible approach to OSH surveillance evaluation. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-022-12895-6. BioMed Central 2022-03-14 /pmc/articles/PMC8922762/ /pubmed/35287647 http://dx.doi.org/10.1186/s12889-022-12895-6 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Yang, Liu
Branscum, Adam
Kincl, Laurel
Understanding occupational safety and health surveillance: expert consensus on components, attributes and example measures for an evaluation framework
title Understanding occupational safety and health surveillance: expert consensus on components, attributes and example measures for an evaluation framework
title_full Understanding occupational safety and health surveillance: expert consensus on components, attributes and example measures for an evaluation framework
title_fullStr Understanding occupational safety and health surveillance: expert consensus on components, attributes and example measures for an evaluation framework
title_full_unstemmed Understanding occupational safety and health surveillance: expert consensus on components, attributes and example measures for an evaluation framework
title_short Understanding occupational safety and health surveillance: expert consensus on components, attributes and example measures for an evaluation framework
title_sort understanding occupational safety and health surveillance: expert consensus on components, attributes and example measures for an evaluation framework
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8922762/
https://www.ncbi.nlm.nih.gov/pubmed/35287647
http://dx.doi.org/10.1186/s12889-022-12895-6
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